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To mitigate Urban Heat Island effects, we need a better understanding of how urban land use configurations contribute to land surface temperatures and how the cooling effects of green and blue infrastructure work in different urban contexts. With the availability of detailed data on land surface temperature, land cover, vegetation/tree canopy, and water bodies, machine learning models are now widely used to model the cooling effects of green and blue infrastructure in urban areas. For example, studies have shown that landscape manipulation by varying the configuration of natural and built areas can significantly reduce land surface temperature.